The present invention relates to a phoneme dividing method using a multilevel neural network.
Conventional phoneme dividing technologies complicate their systems by finding the border of phonemes through an analysis utilizing prefixed various phonetic knowledge and rules after extracting the frequency component, that is, the spectrogram, from an acoustic signal.
Without an effective and optimal method for combining various knowledge and rules used in phoneme division, the performance of system is not reliable and drastically deteriorated depending upon the and any changes therein of situation.
There is a method for finding the border of a phoneme by comparing characteristic patterns with an incoming signal in phoneme division after previously extracting the characteristics of all phonemes and storing them in patterns. This method requires information regarding the characteristic patterns for all phonemes to undesirably increase the volume of memory of the system and also the amount of calculation in performance.